OpenRaiser/Intern-Atlas huggingface dataset:
Online Fault-Tolerant Dynamic Event Region Detection in Sensor Networks via Trust Model
Venue: arXiv cs.DC 2016
Year: 2016

This paper proposes a Bayesian modeling approach to address the problem of online fault-tolerant dynamic event region detection in wireless sensor networks. In our model every network node is associated with a virtual community and a trust index, which quantitatively measures the trustworthiness of this node in its community. If a sensor node's trust value is smaller than a threshold, it suggests that this node encounters a fault and thus its sensor reading can not be trusted at this moment. This concept of sensor node trust discriminates our model with the other alternatives, e.g.,the Markov random fields. The practical issues, including spatiotemporal correlations of neighbor nodes' sensor readings, the presence of sensor faults and the requirement of online processing are linked together by the concept trust and are all taken into account in the modeling stage. Based on the proposed model, the trust value of each node is updated online by a particle filter algorithm upon the arrival of new observations. The decision on whether a node is located in the event region is made based upon the current estimate of this node's trust value. Experimental results demonstrate that the proposed solution can provide striking better performance than existent methods in terms of error rate in detecting the event region.
Learning Macro-actions for State-Space Planning
Venue: arXiv cs.AI 2016
Year: 2016

Planning has achieved significant progress in recent years. Among the various approaches to scale up plan synthesis, the use of macro-actions has been widely explored. As a first stage towards the development of a solution to learn on-line macro-actions, we propose an algorithm to identify useful macro-actions based on data mining techniques. The integration in the planning search of these learned macro-actions shows significant improvements over four classical planning benchmarks.
Welcome or Not-Welcome: Reactions to Refugee Situation on Social Media
Venue: arXiv cs.SI 2016
Year: 2016

For many European countries, in 2015 the refugee situation developed from a remote tragedy reported upon in the news to a situation they have to deal with in their own neighborhood. Driven by this observation, we investigated the development of the perception of the refugee situation during 2015 in Twitter. Starting from a dataset of 1.7 Million tweets covering refugee-related topics from May to December 2015, we investigated how the discussion on refugees changed over time, in different countries as well as in relationship with the evolution of the actual situation. In this paper we report and discuss our findings from checking a set of hypotheses, such as that the closeness to the actual situation would influence the intensity and polarity of discussions and that news media takes a mediating role between the actual and perceived refugee situation.
Unified Control and Data Flow Diagrams Applied to Software Engineering and other Systems
Venue: arXiv cs.SE 2016
Year: 2016

More often than not, there is a need to understand the structure of complex computer code: what functions and in what order they are called, how information travels around static, input, and output variables, what depends on what. As a rule, executable code and data are scattered among multiple files and even multiple modules. Information is transmitted among variables which often change names. These tangled relations greatly complicate the development, maintenance, and redevelopment of code, its analysis for complexity and its robustness. As of now, there is no tool which is capable of presenting the real-life, useful diagram of actual code. Conventional flowcharts fail. Proposed is the method which overcomes these difficulties. The main idea is that functionality of software can be described through flows of control, which is essentially flows of time, and flows of data. These are inseparable. The second idea is to follow very strict system boundaries and distinctions with respect to modules, functions, blocks, and operators, as well as data holders, showing them all as subsystems, in other words, by clearly expressing the system structure when every piece of executable code and every variable may have its own graphical representation. The third is defining timelines as the entities clearly separated from the connected blocks of code. Timelines allow presentation of nesting of the control flow as deep as necessary. As a proof of concept, the same methods successfully describe production systems. Keywords: flowchart, UML, software diagram, visual programming, extreme programming, extreme modeling, control flow, data flow.
Final Service Provider DevOps concept and evaluation
Venue: arXiv cs.NI 2016
Year: 2016

This report presents the results of the UNIFY Service Provider DevOps activities. First, we present the final definition and assessment of the concept. SP-DevOps is realized by a combination of various functional components facilitating integrated service verification, efficient and programmable observability, and automated troubleshooting processes. Our assessment shows that SP-DevOps can help providers to reach a medium level of DevOps maturity and allows significant reduction in OPEX. Second, we focus on the evaluation of the proposed SP-DevOps components. The set of tools proposed supports ops and devs across all stages, with a focus on the deployment, operation and debugging phases, and allows to activate automated processes for operating NFV environments. Finally, we present use-cases and our demonstrators for selected process implementions, which allowed the functional validation of SP-DevOps.
An Automatic System for Acoustic Microphone Geometry Calibration based on Minimal Solvers
Venue: arXiv cs.SD 2016
Year: 2016

In this paper, robust detection, tracking and geometry estimation methods are developed and combined into a system for estimating time-difference estimates, microphone localization and sound source movement. No assumptions on the 3D locations of the microphones and sound sources are made. The system is capable of tracking continuously moving sound sources in an reverberant environment. The multi-path components are explicitly tracked and used in the geometry estimation parts. The system is based on matching between pairs of channels using GCC-PHAT. Instead of taking a single maximum at each time instant from each such pair, we select the four strongest local maxima. This produce a set of hypothesis to work with in the subsequent steps, where consistency constraints between the channels and time-continuity constraints are exploited. In the paper it demonstrated how such detections can be used to estimate microphone positions, sound source movement and room geometry. The methods are tested and verified using real data from several reverberant environments. The evaluation demonstrated accuracy in the order of few millimeters.
InfraNotes: Inconspicuous Handwritten Trajectory Tracking for Lecture Note Recording with Infrared Sensors
Venue: arXiv cs.HC 2016
Year: 2016

Lecture notes are important for students to review and understand the key points in the class. Unfortunately, the students often miss or lose part of the lecture notes. In this paper, we design and implement an infrared sensor based system, InfraNotes, to automatically record the notes on the board by sensing and analyzing hand gestures of the lecturer. Compared with existing techniques, our system does not require special accessories with lecturers such as sensor-facilitated pens, writing surfaces or the video-taping infrastructure. Instead, it only has an infrared-sensor module on the eraser holder of black/white board to capture handwritten trajectories. With a lightweight framework for handwritten trajectory processing, clear lecture notes can be generated automatically. We evaluate the quality of lecture notes by three standard character recognition techniques. The results indicate that InfraNotes is a promising solution to create clear and complete lectures to promote the education.
Perceptually-Driven Video Coding with the Daala Video Codec
Venue: arXiv cs.MM 2016
Year: 2016

The Daala project is a royalty-free video codec that attempts to compete with the best patent-encumbered codecs. Part of our strategy is to replace core tools of traditional video codecs with alternative approaches, many of them designed to take perceptual aspects into account, rather than optimizing for simple metrics like PSNR. This paper documents some of our experiences with these tools, which ones worked and which did not. We evaluate which tools are easy to integrate into a more traditional codec design, and show results in the context of the codec being developed by the Alliance for Open Media.
Computational linking theory
Venue: arXiv cs.CL 2016
Year: 2016

A linking theory explains how verbs' semantic arguments are mapped to their syntactic arguments---the inverse of the Semantic Role Labeling task from the shallow semantic parsing literature. In this paper, we develop the Computational Linking Theory framework as a method for implementing and testing linking theories proposed in the theoretical literature. We deploy this framework to assess two cross-cutting types of linking theory: local v. global models and categorical v. featural models. To further investigate the behavior of these models, we develop a measurement model in the spirit of previous work in semantic role induction: the Semantic Proto-Role Linking Model. We use this model, which implements a generalization of Dowty's seminal Proto-Role Theory, to induce semantic proto-roles, which we compare to those Dowty proposes.
Performance Bounds for Remote Estimation under Energy Harvesting Constraints
Venue: arXiv cs.IT 2016
Year: 2016

Remote estimation with an energy harvesting sensor with a limited data and energy buffer is considered. The sensor node observes an unknown Gaussian field and communicates its observations to a remote fusion center using the energy it harvested. The fusion center employs minimum mean-square error (MMSE) estimation to reconstruct the unknown field. The distortion minimization problem under the online scheme, where the sensor has access to only the statistical information for the future energy packets is considered. We provide performance bounds on the achievable distortion under a slotted block transmission scheme, where at each transmission time slot, the data and the energy buffer are completely emptied. Our bounds provide insights to the trade-offs between the buffer sizes, the statistical properties of the energy harvesting process and the achievable distortion. In particular, these trade-offs illustrate the insensitivity of the performance to the buffer sizes for signals with low degree of freedom and suggest performance improvements with increasing buffer size for signals with relatively higher degree of freedom. Depending only on the mean, variance and finite support of the energy arrival process, these results provide practical insights for the battery and buffer sizes for deployment in future energy harvesting wireless sensing systems.
Mining the Web for Pharmacovigilance: the Case Study of Duloxetine and Venlafaxine
Venue: arXiv cs.CL 2016
Year: 2016

Adverse reactions caused by drugs following their release into the market are among the leading causes of death in many countries. The rapid growth of electronically available health related information, and the ability to process large volumes of them automatically, using natural language processing (NLP) and machine learning algorithms, have opened new opportunities for pharmacovigilance. Survey found that more than 70% of US Internet users consult the Internet when they require medical information. In recent years, research in this area has addressed for Adverse Drug Reaction (ADR) pharmacovigilance using social media, mainly Twitter and medical forums and websites. This paper will show the information which can be collected from a variety of Internet data sources and search engines, mainly Google Trends and Google Correlate. While considering the case study of two popular Major depressive Disorder (MDD) drugs, Duloxetine and Venlafaxine, we will provide a comparative analysis for their reactions using publicly-available alternative data sources.
Modeling, implementation and performance analysis of mobility load balancing for LTE downlink data transmission
Venue: arXiv cs.NI 2016
Year: 2016

We propose in this paper a simulation implementation of self-organizing Networks optimization related to mobility load balancing (MLB) for lte systems using ns-3. the implementation is achieved toward two MLB algorithms dynamically adjusting handover (HO) parameters based on the reference signal received power measurements. such adjustments are done with respect to loads of both an overloaded cell and its cell neighbours having enough available resources enabling to achieve load balancing. numerical investigations through selected key performance indicators of the proposed MLB algorithms when compared with another HO algorithm (already implemented in ns3) based on A3 event highlight the significant MLB gains provided in terms global network throughput, packet loss rate and the number of successful HO without incurring significant overhead.
Doing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing
Venue: arXiv cs.OH 2016
Year: 2016

Energy and power consumption are major limitations to continued scaling of computing systems. Inexactness, where the quality of the solution can be traded for energy savings, has been proposed as an approach to overcoming those limitations. In the past, however, inexactness necessitated the need for highly customized or specialized hardware. The current evolution of commercial off-the-shelf(COTS) processors facilitates the use of lower-precision arithmetic in ways that reduce energy consumption. We study these new opportunities in this paper, using the example of an inexact Newton algorithm for solving nonlinear equations. Moreover, we have begun developing a set of techniques we call reinvestment that, paradoxically, use reduced precision to improve the quality of the computed result: They do so by reinvesting the energy saved by reduced precision.
Zero Shot Hashing
Venue: arXiv cs.CV 2016
Year: 2016

This paper provides a framework to hash images containing instances of unknown object classes. In many object recognition problems, we might have access to huge amount of data. It may so happen that even this huge data doesn't cover the objects belonging to classes that we see in our day to day life. Zero shot learning exploits auxiliary information (also called as signatures) in order to predict the labels corresponding to unknown classes. In this work, we attempt to generate the hash codes for images belonging to unseen classes, information of which is available only through the textual corpus. We formulate this as an unsupervised hashing formulation as the exact labels are not available for the instances of unseen classes. We show that the proposed solution is able to generate hash codes which can predict labels corresponding to unseen classes with appreciably good precision.
Computing Majority by Constant Depth Majority Circuits with Low Fan-in Gates
Venue: arXiv cs.CC 2016
Year: 2016

We study the following computational problem: for which values of $k$, the majority of $n$ bits $\text{MAJ}_n$ can be computed with a depth two formula whose each gate computes a majority function of at most $k$ bits? The corresponding computational model is denoted by $\text{MAJ}_k \circ \text{MAJ}_k$. We observe that the minimum value of $k$ for which there exists a $\text{MAJ}_k \circ \text{MAJ}_k$ circuit that has high correlation with the majority of $n$ bits is equal to $Θ(n^{1/2})$. We then show that for a randomized $\text{MAJ}_k \circ \text{MAJ}_k$ circuit computing the majority of $n$ input bits with high probability for every input, the minimum value of $k$ is equal to $n^{2/3+o(1)}$. We show a worst case lower bound: if a $\text{MAJ}_k \circ \text{MAJ}_k$ circuit computes the majority of $n$ bits correctly on all inputs, then $k\geq n^{13/19+o(1)}$. This lower bound exceeds the optimal value for randomized circuits and thus is unreachable for pure randomized techniques. For depth $3$ circuits we show that a circuit with $k= O(n^{2/3})$ can compute $\text{MAJ}_n$ correctly on all inputs.
Egocentric Height Estimation
Venue: arXiv cs.CV 2016
Year: 2016

Egocentric, or first-person vision which became popular in recent years with an emerge in wearable technology, is different than exocentric (third-person) vision in some distinguishable ways, one of which being that the camera wearer is generally not visible in the video frames. Recent work has been done on action and object recognition in egocentric videos, as well as work on biometric extraction from first-person videos. Height estimation can be a useful feature for both soft-biometrics and object tracking. Here, we propose a method of estimating the height of an egocentric camera without any calibration or reference points. We used both traditional computer vision approaches and deep learning in order to determine the visual cues that results in best height estimation. Here, we introduce a framework inspired by two stream networks comprising of two Convolutional Neural Networks, one based on spatial information, and one based on information given by optical flow in a frame. Given an egocentric video as an input to the framework, our model yields a height estimate as an output. We also incorporate late fusion to learn a combination of temporal and spatial cues. Comparing our model with other methods we used as baselines, we achieve height estimates for videos with a Mean Average Error of 14.04 cm over a range of 103 cm of data, and classification accuracy for relative height (tall, medium or short) up to 93.75% where chance level is 33%.
Distributed pursuit algorithms for probabilistic adversaries on connected graphs
Venue: arXiv cs.DM 2016
Year: 2016

A gambler moves between the vertices $1, \ldots, n$ of a graph using the probability distribution $p_{1}, \ldots, p_{n}$. Multiple cops pursue the gambler on the graph, only being able to move between adjacent vertices. We investigate the expected capture time for the gambler against $k$ cops as a function of $n$ and $k$ for three versions of the game: (1) known gambler: the cops know the gambler's distribution (2) unknown gambler: the cops do not know the gambler's distribution (3) known changing gambler: the gambler's distribution can change every turn, but the cops know all of the gambler's distributions from the beginning. We show for $n > k$ that if the cops are allowed to choose their initial positions before the game starts and before they know the gambler's distribution(s), and if both the gambler and the cops play optimally, then the expected capture time is $Θ(n/k)$ for the known gambler, the unknown gambler, and the known changing gambler.
Portage: Bringing Hackers' Wisdom to Science
Venue: arXiv cs.DC 2016
Year: 2016

Providing users of HPC systems with a wide variety of up to date software packages is a challenging task. Large software stacks built from source are difficult to manage, requiring powerful package management tools. The Portage package manager from Gentoo is a highly flexible tool that offers a mature solution to this otherwise daunting task. The Gentoo Prefix project develops and maintains a way of installing Gentoo systems in non-standard locations, bringing the virtues of Gentoo to other operating systems. Here we demonstrate how a Gentoo Prefix installation can be used to cross compile software packages for the Intel Xeon Phi known as Knights Corner, as well as to manage large software stacks in HPC environments.
A New Theoretical and Technological System of Imprecise-Information Processing
Venue: arXiv cs.CL 2016
Year: 2016

Imprecise-information processing will play an indispensable role in intelligent systems, especially in the anthropomorphic intelligent systems (as intelligent robots). A new theoretical and technological system of imprecise-information processing has been founded in Principles of Imprecise-Information Processing: A New Theoretical and Technological System[1] which is different from fuzzy technology. The system has clear hierarchy and rigorous structure, which results from the formation principle of imprecise information and has solid mathematical and logical bases, and which has many advantages beyond fuzzy technology. The system provides a technological platform for relevant applications and lays a theoretical foundation for further research.
Cross-layer Transmission Design for Tactile Internet
Venue: arXiv cs.IT 2016
Year: 2016

To ensure the low end-to-end (E2E) delay for tactile internet, short frame structures will be used in 5G systems. As such, transmission errors with finite blocklength channel codes should be considered to guarantee the high reliability requirement. In this paper, we study cross-layer transmission optimization for tactile internet, where both queueing delay and transmission delay are accounted for in the E2E delay, and different packet loss/error probabilities are considered to characterize the reliability. We show that the required transmit power becomes unbounded when the allowed maximal queueing delay is shorter than the channel coherence time. To satisfy quality-of-service requirement with finite transmit power, we introduce a proactive packet dropping mechanism, and optimize a queue state information and channel state information dependent transmission policy. Since the resource and policy for transmission and the packet dropping policy are related to the packet error probability, queueing delay violation probability, and packet dropping probability, we optimize the three probabilities and obtain the policies related to these probabilities. We start from single-user scenario and then extend our framework to the multi-user scenario. Simulation results show that the optimized three probabilities are in the same order of magnitude. Therefore, we have to take into account all these factors when we design systems for tactile internet applications.
Automatic Gain Tuning of a Momentum Based Balancing Controller for Humanoid Robots
Venue: arXiv cs.SY 2016
Year: 2016

This paper proposes a technique for automatic gain tuning of a momentum based balancing controller for humanoid robots. The controller ensures the stabilization of the centroidal dynamics and the associated zero dynamics. Then, the closed-loop, constrained joint space dynamics is linearized and the controller's gains are chosen so as to obtain desired properties of the linearized system. Symmetry and positive definiteness constraints of gain matrices are enforced by proposing a tracker for symmetric positive definite matrices. Simulation results are carried out on the humanoid robot iCub.